2016 LOCAL SEO RANKING FACTORS METHODOLOGY

The data points for this study were scraped via repeated Google searches based on keyword and geographic location (city). We partner with Places Scout, the leading local competitive intelligence tool, to be able to gather and process all the data points. While most of the data came via Places Scout’s proprietary software, we also gathered link metrics through both Moz’s Open Site Explorer APIs and Majestic. In 2017 we added in link data from AHREFs

The following keywords were used for the searches for the 2016 version of the study:

In 2017 we expanded the keyword list to:

Auto Parts Store

Bank

Clothing Store

CPA

Dentist

Furniture Stores

Grocery Stores

Hair Salon

Hardware Store

Lawyer

Pharmacy

Plastic Surgeon

Restaurants

Tailor

We chose these keywords both for their high monthly search volumes as well as their mix of SMB’s and national to local brands.

These searches were done in 100 cities chosen by population size from this list. We looked at cities 1-50 as well as 100-150 in an attempt to look at both highly competitive and normally competitive markets. For 2017 we looked at the top 150 cities.

Lastly, we performed three permutations of every search in order to explore the full scope of keyword + geo local searches. The permutations are as follows:

The end result is that we looked at ~3000 local searches, ~30,000 Google My Business listings, websites, link and citations profiles which gave us over a million quantitative data points to analyze in what we think is the largest empirical study of Local SEO ranking factors ever done outside of Google.

Two statistical methods were employed to properly correlate the data. First Kendell’s Tau-b was used to analyze ordinal variables (continuous or integer independent variables) while the Kruskal-Wallis test was used for categorical independent variables. If you are one of the 3 people reading this who wants to know more information you can contact me at dan {at} localseoguide.com.